Understanding Graph Database Patterns

SHOW: 405

DESCRIPTION: Aaron and Brian talk with Emil Eifrem, (@emileifrem, Founder/CTO @Neo4j) about the emergence of graph databases, common use-cases, and how developers are thinking about new ways to leverage graph databases.  

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CLOUD NEWS OF THE WEEK:

• IBM closes acquisition of Red Hat ($34B)
• Cisco acquires Acacia (Optical Networking - $2.6B)
• Google Cloud acquires Elastifile ($200M)
• Microsoft and ServiceNow announce strategic partnership
• Microsoft joins hospital chain Providence to build “hospital of the future”

SHOW INTERVIEW LINKS:

• Neo4j Homepage
• Neo4j Open Source

SHOW NOTES:

Topic 1 - Welcome to the show. You’ve been the CEO of Neo4j for over a decade now. How has the landscape around application-usage of data changed in the most significant ways? 

Topic 2 - For many decades, most data-centric applications were built around Relational Databases (SQL Databases). These days, application patterns and use-cases have expanded significantly. How do graph databases fit into these new trends? 

Topic 3 - With all the new patterns emerging, there are both business reasons and technical reasons for choosing the right database platform. How do you find the business-level thought process happening (contributing, influencing) around platform choice? How do you find the technical-level thought process happening (contributing, influencing) around platform choice?

Topic 4 - Every company that’s involved with the commercialization of open source projects is trying to figure out the best way to manage a portfolio between OSS, software offerings and cloud offerings. How does Neo4j think about that balance? 

Topic 5 - Getting developer momentum and mass around a set of patterns is critical. How does Neo4j think about enabling developers, and what are some of the things you’ve done to accelerate their success and consistent learning? 

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